Literature DB >> 25304818

The role of linkage disequilibrium in case-only studies of gene-environment interactions.

Pankaj Yadav1, Sandra Freitag-Wolf, Wolfgang Lieb, Michael Krawczak.   

Abstract

Gene-environment (G × E) interactions have been invoked to account, at least in part, for the gap between the known heritability of common human diseases and the phenotypic variation hitherto explained by genetic variants. Noteworthy in this context, a case-only (CO) design has been proposed in the past as a means to detect G × E interactions possibly more efficiently than by using classical case-control and cohort designs. So far, however, most CO studies have followed a candidate (or single) gene approach, and the genome-wide utility of the CO design is still more or less unknown. In particular, the way in which linkage disequilibrium (LD) impacts upon the chance to detect G × E interaction through the analysis of proxy markers has not been studied in much detail before. Therefore, we systematically assessed the power to indirectly detect a given G × E interaction through exploiting LD in a CO design. Our simulations revealed a strong relationship between LD and detection power that was subsequently validated in a real colorectal cancer data set.

Entities:  

Mesh:

Year:  2014        PMID: 25304818     DOI: 10.1007/s00439-014-1497-2

Source DB:  PubMed          Journal:  Hum Genet        ISSN: 0340-6717            Impact factor:   4.132


  29 in total

Review 1.  Epistasis: what it means, what it doesn't mean, and statistical methods to detect it in humans.

Authors:  Heather J Cordell
Journal:  Hum Mol Genet       Date:  2002-10-01       Impact factor: 6.150

2.  Sample size needed to detect gene-gene interactions using association designs.

Authors:  Shuang Wang; Hongyu Zhao
Journal:  Am J Epidemiol       Date:  2003-11-01       Impact factor: 4.897

Review 3.  Gene-environment interactions in human diseases.

Authors:  David J Hunter
Journal:  Nat Rev Genet       Date:  2005-04       Impact factor: 53.242

4.  Genetic model testing and statistical power in population-based association studies of quantitative traits.

Authors:  Guillaume Lettre; Christoph Lange; Joel N Hirschhorn
Journal:  Genet Epidemiol       Date:  2007-05       Impact factor: 2.135

Review 5.  Effect modification and the limits of biological inference from epidemiologic data.

Authors:  W D Thompson
Journal:  J Clin Epidemiol       Date:  1991       Impact factor: 6.437

6.  Using principal components of genetic variation for robust and powerful detection of gene-gene interactions in case-control and case-only studies.

Authors:  Samsiddhi Bhattacharjee; Zhaoming Wang; Julia Ciampa; Peter Kraft; Stephen Chanock; Kai Yu; Nilanjan Chatterjee
Journal:  Am J Hum Genet       Date:  2010-03-04       Impact factor: 11.025

7.  Genome-wide association study identifies three new susceptibility loci for esophageal squamous-cell carcinoma in Chinese populations.

Authors:  Chen Wu; Zhibin Hu; Zhonghu He; Weihua Jia; Feng Wang; Yifeng Zhou; Zhihua Liu; Qimin Zhan; Yu Liu; Dianke Yu; Kan Zhai; Jiang Chang; Yan Qiao; Guangfu Jin; Zhe Liu; Yuanyuan Shen; Chuanhai Guo; Jianhua Fu; Xiaoping Miao; Wen Tan; Hongbing Shen; Yang Ke; Yixin Zeng; Tangchun Wu; Dongxin Lin
Journal:  Nat Genet       Date:  2011-06-05       Impact factor: 38.330

8.  Non-hierarchical logistic models and case-only designs for assessing susceptibility in population-based case-control studies.

Authors:  W W Piegorsch; C R Weinberg; J A Taylor
Journal:  Stat Med       Date:  1994-01-30       Impact factor: 2.373

Review 9.  PopGen: population-based recruitment of patients and controls for the analysis of complex genotype-phenotype relationships.

Authors:  Michael Krawczak; Susanna Nikolaus; Huberta von Eberstein; Peter J P Croucher; Nour Eddine El Mokhtari; Stefan Schreiber
Journal:  Community Genet       Date:  2006

10.  Genome-wide gene-environment study identifies glutamate receptor gene GRIN2A as a Parkinson's disease modifier gene via interaction with coffee.

Authors:  Taye H Hamza; Honglei Chen; Erin M Hill-Burns; Shannon L Rhodes; Jennifer Montimurro; Denise M Kay; Albert Tenesa; Victoria I Kusel; Patricia Sheehan; Muthukrishnan Eaaswarkhanth; Dora Yearout; Ali Samii; John W Roberts; Pinky Agarwal; Yvette Bordelon; Yikyung Park; Liyong Wang; Jianjun Gao; Jeffery M Vance; Kenneth S Kendler; Silviu-Alin Bacanu; William K Scott; Beate Ritz; John Nutt; Stewart A Factor; Cyrus P Zabetian; Haydeh Payami
Journal:  PLoS Genet       Date:  2011-08-18       Impact factor: 5.917

View more
  4 in total

1.  Allowing for population stratification in case-only studies of gene-environment interaction, using genomic control.

Authors:  Pankaj Yadav; Sandra Freitag-Wolf; Wolfgang Lieb; Astrid Dempfle; Michael Krawczak
Journal:  Hum Genet       Date:  2015-08-22       Impact factor: 4.132

2.  A genome-wide case-only test for the detection of digenic inheritance in human exomes.

Authors:  Gaspard Kerner; Matthieu Bouaziz; Aurélie Cobat; Benedetta Bigio; Andrew T Timberlake; Jacinta Bustamante; Richard P Lifton; Jean-Laurent Casanova; Laurent Abel
Journal:  Proc Natl Acad Sci U S A       Date:  2020-07-27       Impact factor: 11.205

3.  Genetic Factors Interact With Tobacco Smoke to Modify Risk for Inflammatory Bowel Disease in Humans and Mice.

Authors:  Pankaj Yadav; David Ellinghaus; Gaëlle Rémy; Sandra Freitag-Wolf; Anabelle Cesaro; Frauke Degenhardt; Gabrielle Boucher; Myriam Delacre; Laurent Peyrin-Biroulet; Muriel Pichavant; John D Rioux; Philippe Gosset; Andre Franke; L Philip Schumm; Michael Krawczak; Mathias Chamaillard; Astrid Dempfle; Vibeke Andersen
Journal:  Gastroenterology       Date:  2017-05-12       Impact factor: 22.682

4.  Genotype imputation in case-only studies of gene-environment interaction: validity and power.

Authors:  Milda Aleknonytė-Resch; Silke Szymczak; Sandra Freitag-Wolf; Astrid Dempfle; Michael Krawczak
Journal:  Hum Genet       Date:  2021-05-26       Impact factor: 4.132

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.